Frustrated with sparking quick, fun conversations in your AI agency community? This or That templates are a proven way to break the ice, encourage participation, and keep engagement lively. Discover ready-to-use prompts that make it easy to get members talking in seconds.
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This or That posts tap into our instinct for quick choices and friendly competition. The low-pressure format makes it easy for even the shyest members to join in, since answers are fast, require little thought, and feel playful. By inviting members to pick between two clear options, you lower the barrier to participation, spark curiosity, and create space for friendly debate.
For AI agency communities, these prompts are especially powerful. They allow members to reveal their tech habits, preferences, and personalities without committing to long explanations. This means more comments, more connections, and a more vibrant group culture. Plus, the fun tone sets a relaxed mood, which is ideal for social spaces built around complex topics like AI.
Chatbot or virtual assistant - which would you rather build?
💡 Example: "Chatbot or virtual assistant - which would you rather build?"
Would you choose an AI that writes code or one that creates art? Tell us why!
💡 Example: "Would you choose an AI that writes code or one that creates art? Tell us why!"
Automation or personalization - which matters more in your projects?
💡 Example: "Automation or personalization - which matters more in your projects?"
Text analysis or image recognition - which AI skill excites you more?
💡 Example: "Text analysis or image recognition - which AI skill excites you more?"
Early adopter or wait-and-see - how do you approach new AI tech?
💡 Example: "Early adopter or wait-and-see - how do you approach new AI tech?"
Would you rather train data or tune models all day?
💡 Example: "Would you rather train data or tune models all day?"
Remote brainstorms or in-person whiteboard sessions - what is your team vibe?
💡 Example: "Remote brainstorms or in-person whiteboard sessions - what is your team vibe?"
Big data or small, curated datasets - which do you prefer to work with?
💡 Example: "Big data or small, curated datasets - which do you prefer to work with?"
Explainable AI or black box models - which do you trust more?
💡 Example: "Explainable AI or black box models - which do you trust more?"
AI for productivity or for creativity - which do you use more?
💡 Example: "AI for productivity or for creativity - which do you use more?"
Morning sprints or late-night coding - when do you do your best AI work?
💡 Example: "Morning sprints or late-night coding - when do you do your best AI work?"
Would you rather deploy fast or perfect your project before launch?
💡 Example: "Would you rather deploy fast or perfect your project before launch?"
AI-powered emails or chatbots - which do you think saves more time?
💡 Example: "AI-powered emails or chatbots - which do you think saves more time?"
Debugging code or testing models - which task do you enjoy more?
💡 Example: "Debugging code or testing models - which task do you enjoy more?"
Solo developer or team player - how do you prefer to work on AI projects?
💡 Example: "Solo developer or team player - how do you prefer to work on AI projects?"
Would you rather present to clients or work behind the scenes?
💡 Example: "Would you rather present to clients or work behind the scenes?"
Slack or Discord - which platform is better for your team?
💡 Example: "Slack or Discord - which platform is better for your team?"
Quick prototype or detailed planning - which approach fits your agency?
💡 Example: "Quick prototype or detailed planning - which approach fits your agency?"
Open-source tools or custom solutions - what do you prefer for AI work?
💡 Example: "Open-source tools or custom solutions - what do you prefer for AI work?"
Would you rather improve existing models or build new ones from scratch?
💡 Example: "Would you rather improve existing models or build new ones from scratch?"
Working with structured data or unstructured data - which is more fun?
💡 Example: "Working with structured data or unstructured data - which is more fun?"
Machine learning or deep learning - which do you use more often?
💡 Example: "Machine learning or deep learning - which do you use more often?"
Would you pick learning Python or R for your next skill?
💡 Example: "Would you pick learning Python or R for your next skill?"
On-site client meetings or virtual demos - which do you prefer?
💡 Example: "On-site client meetings or virtual demos - which do you prefer?"
Agile sprints or waterfall planning - how does your team roll?
💡 Example: "Agile sprints or waterfall planning - how does your team roll?"
Would you rather automate emails or automate reports first?
💡 Example: "Would you rather automate emails or automate reports first?"
Data privacy or model accuracy - which matters more for your clients?
💡 Example: "Data privacy or model accuracy - which matters more for your clients?"
Early morning coffee or late-night energy drink - your coding fuel?
💡 Example: "Early morning coffee or late-night energy drink - your coding fuel?"
Would you rather attend an AI conference or take an online course?
💡 Example: "Would you rather attend an AI conference or take an online course?"
Voice assistants or recommendation engines - which impresses you more?
💡 Example: "Voice assistants or recommendation engines - which impresses you more?"
Would you rather have a robot teammate or an AI mentor?
💡 Example: "Would you rather have a robot teammate or an AI mentor?"
In-person hackathons or virtual coding jams - which would you join?
💡 Example: "In-person hackathons or virtual coding jams - which would you join?"
Would you rather read AI research papers or watch explainer videos?
💡 Example: "Would you rather read AI research papers or watch explainer videos?"
Quick answers or deep dives - what do you look for in community posts?
💡 Example: "Quick answers or deep dives - what do you look for in community posts?"
Would you rather automate your calendar or your email inbox?
💡 Example: "Would you rather automate your calendar or your email inbox?"
AI for business growth or AI for social good - which motivates you more?
💡 Example: "AI for business growth or AI for social good - which motivates you more?"
Would you rather use a cutting-edge new AI tool or stick with a proven classic?
💡 Example: "Would you rather use a cutting-edge new AI tool or stick with a proven classic?"
Team brainstorming or solo research - how do you solve tough AI problems?
💡 Example: "Team brainstorming or solo research - how do you solve tough AI problems?"
Would you rather code in silence or with background music?
💡 Example: "Would you rather code in silence or with background music?"
AI-generated art or AI-generated music - which blows your mind more?
💡 Example: "AI-generated art or AI-generated music - which blows your mind more?"
Would you rather ship a small feature today or wait for a big launch later?
💡 Example: "Would you rather ship a small feature today or wait for a big launch later?"
Ask why you chose your answer - what made you pick it?
💡 Example: "Ask why you chose your answer - what made you pick it?"
To use these templates, simply copy and paste your favorite prompt into your community platform. Customize the options to match current trends or your specific audience if needed. Pin a This or That post for new members to introduce themselves, or schedule regular prompts to keep conversations fresh. Encourage replies by commenting yourself and tagging a few members to kick things off. Rotate topics to keep things interesting and avoid repetition.
For all platforms, keep posts concise and visually clean. Use emojis to make options pop if your platform supports them. Tag or mention members to prompt participation. If polls are available, use them for quick clicks, but written posts encourage more discussion. Adjust posting frequency based on your group's activity level.
To engage your AI agency community, craft 'This or That' prompts that compare widely used AI frameworks, such as 'TensorFlow or PyTorch for rapid prototyping?' or 'Preferred for production deployments: TensorFlow or PyTorch?' This not only sparks discussion among technical team members but also surfaces preferences and experiences relevant to current and future client projects.
Absolutely. Framing 'This or That' posts around application domains—such as 'Prioritizing NLP vs Computer Vision for upcoming client pitches?'—can drive higher-level strategy conversations. This helps your community align on agency strengths and market trends, while also encouraging members to share insights on implementation challenges and business impact.
You can create posts like 'OpenAI GPT-4 API or open-source Llama 2 for client chatbots?' This type of comparison is highly relevant to agency workflows, since it invites nuanced discussion about trade-offs in cost, customization, performance, and compliance—factors pivotal in client solution architecture.
Pose questions like 'For initial model training: synthetic data or real-world datasets?' to spark conversation about data availability, quality, and ethical considerations. These prompts resonate with AI agency professionals who routinely deal with data privacy, annotation costs, and generalization challenges.
Yes! Posts like 'Faster iteration: cloud-based or on-premise deployment?' tap into practical concerns of AI agencies, from scalability to client data security. Expect lively discussions, as deployment infrastructure often impacts project timelines and client satisfaction.
Set clear community guidelines before posting, encouraging respectful sharing of experiences and data-driven arguments. Consider following up with summary posts that highlight key points from both sides. This approach maintains a collaborative atmosphere while leveraging the passion of members for tools central to agency operations.
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